The COVID-19 Situation Report is a data intensive report that tries to portray an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic. If you would like to add additional metrics to this report, please send a mail to the author at .

Date of Report

Numbers as on EOD 

## [1] "2020-05-31"

COVID-19 Overall Stats (Worldwide)

Overall Confirmed Cases Count Worldwide 

## [1] "6166946 (up from 6059017 yesterday: 1.78 % increase)"

Overall Deaths Worldwide

Please note that the deaths is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] "372035 (up from 369126 yesterday: 0.79 % increase)"

Overall Fatality Rate Worldwide in %

Please note that the fatality rate is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] 6.03



In- Depth Country Wise Stats (With Atleast 1000 COVID-19 Confirmations)

Overall Confirmed Cases and Deaths- Country Wise (With Fatality Rates)

Country_Region TotalConfirmed NewConfirmations CasesPercentIncrease TotalDeaths NewDeaths DeathsPercentIncrease FatalityRate
US 1790172 20007 1.13 104381 605 0.58 5.83
Brazil 514849 16409 3.29 29314 480 1.66 5.69
Russia 405843 9268 2.34 4693 138 3.03 1.16
United Kingdom 276156 1937 0.71 38571 113 0.29 13.97
Spain 239479 251 0.10 27127 2 0.01 11.33
Italy 232997 333 0.14 33415 75 0.22 14.34
India 190609 8782 4.83 5408 223 4.30 2.84
France 189009 257 0.14 28805 31 0.11 15.24
Germany 183410 221 0.12 8540 10 0.12 4.66
Peru 164476 8805 5.66 4506 135 3.09 2.74
Turkey 163942 839 0.51 4540 25 0.55 2.77
Iran 151466 2516 1.69 7797 63 0.81 5.15
Chile 99688 4830 5.09 1054 57 5.72 1.06
Canada 92479 798 0.87 7374 215 3.00 7.97
Mexico 90664 3152 3.60 9930 151 1.54 10.95
Saudi Arabia 85261 1877 2.25 503 23 4.79 0.59
China 84146 18 0.02 4638 0 0.00 5.51
Pakistan 69496 3039 4.57 1483 88 6.31 2.13
Belgium 58381 195 0.34 9467 14 0.15 16.22
Qatar 56910 1648 2.98 38 2 5.56 0.07
Bangladesh 47153 2545 5.71 650 40 6.56 1.38
Netherlands 46645 185 0.40 5975 5 0.08 12.81
Belarus 42556 898 2.16 235 6 2.62 0.55
Ecuador 39098 527 1.37 3358 24 0.72 8.59
Sweden 37542 429 1.16 4395 0 0.00 11.71
Singapore 34884 518 1.51 23 0 0.00 0.07
United Arab Emirates 34557 661 1.95 264 2 0.76 0.76
South Africa 32683 1716 5.54 683 40 6.22 2.09
Portugal 32500 297 0.92 1410 14 1.00 4.34
Switzerland 30862 17 0.06 1920 1 0.05 6.22
Colombia 27219 485 1.81 916 25 2.81 3.37
Kuwait 27043 851 3.25 212 7 3.41 0.78
Indonesia 26473 700 2.72 1613 40 2.54 6.09
Ireland 24990 61 0.24 1652 1 0.06 6.61
Egypt 24985 1536 6.55 959 46 5.04 3.84
Poland 23786 215 0.91 1064 3 0.28 4.47
Ukraine 23672 468 2.02 708 12 1.72 2.99
Romania 19257 124 0.65 1266 7 0.56 6.57
Philippines 18086 862 5.00 957 7 0.74 5.29
Dominican Republic 17285 377 2.23 502 4 0.80 2.90
Israel 17071 59 0.35 285 1 0.35 1.67
Argentina 16851 637 3.93 539 11 2.08 3.20
Japan 16751 35 0.21 898 4 0.45 5.36
Austria 16731 46 0.28 668 0 0.00 3.99
Afghanistan 15205 680 4.68 257 8 3.21 1.69
Panama 13463 445 3.42 336 6 1.82 2.50
Denmark 11869 36 0.30 574 3 0.53 4.84
Korea, South 11503 35 0.31 271 1 0.37 2.36
Oman 11437 1014 9.73 49 7 16.67 0.43
Serbia 11412 31 0.27 243 1 0.41 2.13
Bahrain 11398 605 5.61 19 2 11.76 0.17
Kazakhstan 10858 476 4.58 40 2 5.26 0.37
Nigeria 10162 307 3.12 287 14 5.13 2.82
Bolivia 9982 390 4.07 313 3 0.97 3.14
Algeria 9394 127 1.37 653 7 1.08 6.95
Armenia 9282 355 3.98 131 4 3.15 1.41
Czechia 9268 38 0.41 320 1 0.31 3.45
Norway 8440 3 0.04 236 0 0.00 2.80
Moldova 8251 153 1.89 295 4 1.37 3.58
Ghana 8070 302 3.89 36 1 2.86 0.45
Malaysia 7819 57 0.73 115 0 0.00 1.47
Morocco 7807 27 0.35 205 1 0.49 2.63
Australia 7202 10 0.14 103 0 0.00 1.43
Finland 6859 33 0.48 320 4 1.27 4.67
Iraq 6439 260 4.21 205 10 5.13 3.18
Cameroon 5904 0 0.00 191 0 0.00 3.24
Azerbaijan 5494 248 4.73 63 2 3.28 1.15
Honduras 5202 108 2.12 212 11 5.47 4.08
Guatemala 5087 348 7.34 108 6 5.88 2.12
Sudan 5026 226 4.71 286 24 9.16 5.69
Luxembourg 4018 2 0.05 110 0 0.00 2.74
Tajikistan 3930 123 3.23 47 0 0.00 1.20
Hungary 3876 9 0.23 526 2 0.38 13.57
Guinea 3706 0 0.00 23 0 0.00 0.62
Senegal 3645 110 3.11 42 0 0.00 1.15
Uzbekistan 3623 77 2.17 15 1 7.14 0.41
Djibouti 3354 160 5.01 24 2 9.09 0.72
Thailand 3081 4 0.13 57 0 0.00 1.85
Congo (Kinshasa) 3070 104 3.51 72 3 4.35 2.35
Greece 2917 2 0.07 175 0 0.00 6.00
Cote d’Ivoire 2833 34 1.21 33 0 0.00 1.16
Gabon 2655 0 0.00 17 0 0.00 0.64
El Salvador 2517 122 5.09 46 0 0.00 1.83
Bulgaria 2513 14 0.56 140 1 0.72 5.57
Bosnia and Herzegovina 2510 16 0.64 153 0 0.00 6.10
Croatia 2246 0 0.00 103 0 0.00 4.59
North Macedonia 2226 62 2.87 133 2 1.53 5.97
Haiti 2124 259 13.89 44 3 7.32 2.07
Cuba 2045 20 0.99 83 0 0.00 4.06
Somalia 1976 60 3.13 78 5 6.85 3.95
Kenya 1962 74 3.92 64 1 1.59 3.26
Estonia 1869 4 0.21 68 1 1.49 3.64
Iceland 1806 0 0.00 10 0 0.00 0.55
Maldives 1773 101 6.04 5 0 0.00 0.28
Kyrgyzstan 1748 26 1.51 16 0 0.00 0.92
Lithuania 1675 5 0.30 70 0 0.00 4.18
Sri Lanka 1633 13 0.80 10 0 0.00 0.61
Nepal 1572 171 12.21 8 2 33.33 0.51
Slovakia 1521 0 0.00 28 0 0.00 1.84
Venezuela 1510 51 3.50 14 0 0.00 0.93
New Zealand 1504 0 0.00 22 0 0.00 1.46
Slovenia 1473 0 0.00 108 0 0.00 7.33
Equatorial Guinea 1306 0 0.00 12 0 0.00 0.92
Mali 1265 15 1.20 77 1 1.32 6.09
Guinea-Bissau 1256 0 0.00 8 0 0.00 0.64
Lebanon 1220 29 2.43 27 1 3.85 2.21
Ethiopia 1172 109 10.25 11 3 37.50 0.94
Albania 1137 15 1.34 33 0 0.00 2.90
Tunisia 1077 1 0.09 48 0 0.00 4.46
Latvia 1066 1 0.09 24 0 0.00 2.25
Kosovo 1064 0 0.00 30 0 0.00 2.82
Zambia 1057 0 0.00 7 0 0.00 0.66
Costa Rica 1056 9 0.86 10 0 0.00 0.95
Central African Republic 1011 49 5.09 2 1 100.00 0.20

In Depth USA Stats (State Wise Figures)

Confirmed Cases and Deaths- States of USA (With Fatality Rates)

State Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
New York 370770 1110 0.30 29784 74 0.25 8.03 19059.24 1531.03 1 in 52
New Jersey 160445 837 0.52 11698 64 0.55 7.29 18063.68 1317.02 1 in 55
Illinois 120260 1343 1.13 5390 60 1.13 4.48 9490.35 425.35 1 in 105
California 111951 2056 1.87 4172 28 0.68 3.73 2833.33 105.59 1 in 353
Massachusetts 96965 664 0.69 6846 78 1.15 7.06 13952.80 985.11 1 in 72
Pennsylvania 76129 432 0.57 5555 18 0.33 7.30 5946.65 433.92 1 in 168
Texas 64652 1977 3.15 1675 23 1.39 2.59 2229.70 57.77 1 in 448
Michigan 57397 428 0.75 5491 27 0.49 9.57 5747.25 549.82 1 in 174
Florida 56163 739 1.33 2451 4 0.16 4.36 2614.94 114.12 1 in 382
Maryland 52778 763 1.47 2532 23 0.92 4.80 8729.87 418.81 1 in 115
Georgia 47063 732 1.58 2053 49 2.45 4.36 4432.62 193.36 1 in 226
Virginia 44607 996 2.28 1375 5 0.36 3.08 5226.04 161.09 1 in 191
Connecticut 42201 179 0.43 3944 32 0.82 9.35 11836.63 1106.22 1 in 84
Louisiana 39916 339 0.86 2791 5 0.18 6.99 8586.31 600.37 1 in 116
Ohio 35513 480 1.37 2155 6 0.28 6.07 3038.13 184.36 1 in 329
Indiana 34574 363 1.06 2134 9 0.42 6.17 5135.60 316.98 1 in 195
North Carolina 28785 991 3.57 937 8 0.86 3.26 2744.54 89.34 1 in 364
Colorado 26364 280 1.07 1445 2 0.14 5.48 4578.09 250.92 1 in 218
Minnesota 24850 660 2.73 1050 14 1.35 4.23 4406.32 186.18 1 in 227
Tennessee 22566 0 0.00 364 0 0.00 1.61 3302.42 53.27 1 in 303
Washington 21702 353 1.65 1118 0 0.00 5.15 2849.94 146.82 1 in 351
Arizona 19936 678 3.52 907 3 0.33 4.55 2618.03 119.11 1 in 382
Iowa 19552 308 1.60 535 4 0.75 2.74 6197.01 169.57 1 in 161
Wisconsin 18403 173 0.95 592 4 0.68 3.22 3160.71 101.68 1 in 316
Alabama 17952 593 3.42 630 12 1.94 3.51 3661.29 128.49 1 in 273
Mississippi 15523 294 1.93 734 11 1.52 4.73 5215.80 246.63 1 in 192
Rhode Island 14928 109 0.74 718 7 0.98 4.81 14091.51 677.77 1 in 71
Nebraska 14101 196 1.41 170 0 0.00 1.21 7289.57 87.88 1 in 137
Missouri 13438 140 1.05 776 2 0.26 5.77 2189.52 126.44 1 in 457
South Carolina 11861 467 4.10 494 7 1.44 4.16 2303.68 95.95 1 in 434
Utah 9797 264 2.77 113 1 0.89 1.15 3055.87 35.25 1 in 327
Kentucky 9704 0 0.00 431 0 0.00 4.44 2172.05 96.47 1 in 460
Kansas 9700 10 0.10 215 0 0.00 2.22 3329.54 73.80 1 in 300
Delaware 9498 76 0.81 366 5 1.39 3.85 9753.90 375.86 1 in 103
District of Columbia 8801 84 0.96 466 4 0.87 5.29 12470.44 660.29 1 in 80
Nevada 8628 111 1.30 417 0 0.00 4.83 2801.16 135.38 1 in 357
New Mexico 7689 65 0.85 356 5 1.42 4.63 3666.97 169.78 1 in 273
Arkansas 7253 240 3.42 133 0 0.00 1.83 2403.39 44.07 1 in 416
Oklahoma 6418 0 0.00 334 0 0.00 5.20 1621.95 84.41 1 in 617
South Dakota 4993 33 0.67 62 0 0.00 1.24 5643.98 70.08 1 in 177
New Hampshire 4651 159 3.54 245 7 2.94 5.27 3420.58 180.19 1 in 292
Oregon 4243 58 1.39 153 0 0.00 3.61 1005.99 36.28 1 in 994
Puerto Rico 3776 58 1.56 136 3 2.26 3.60 1182.33 42.58 1 in 846
Idaho 2839 36 1.28 82 0 0.00 2.89 1584.21 45.76 1 in 631
North Dakota 2577 23 0.90 61 1 1.67 2.37 3381.61 80.05 1 in 296
Maine 2325 43 1.88 89 0 0.00 3.83 1729.64 66.21 1 in 578
West Virginia 2010 21 1.06 75 0 0.00 3.73 1124.70 41.97 1 in 889
Vermont 981 4 0.41 55 0 0.00 5.61 1572.14 88.14 1 in 636
Wyoming 903 5 0.56 16 0 0.00 1.77 1560.23 27.65 1 in 641
Hawaii 652 1 0.15 17 0 0.00 2.61 460.49 12.01 1 in 2172
Montana 515 10 1.98 17 0 0.00 3.30 481.86 15.91 1 in 2075
Alaska 459 26 6.00 10 0 0.00 2.18 627.44 13.67 1 in 1594

US Tested- Confirmed Funnel (All States)

State Level Figures

State Tested Confirmed ConfirmationRate TestsPerMillPopl
New York 2063825 370770 17.97 106089.83
New Jersey 746145 160445 21.50 84004.62
Illinois 898259 120260 13.39 70886.34
California 1944848 111951 5.76 49221.43
Massachusetts 592853 96965 16.36 85308.69
Pennsylvania 455657 76129 16.71 35592.67
Texas 951865 64652 6.79 32827.59
Michigan 554630 57397 10.35 55535.99
Florida 1021349 56163 5.50 47553.85
Maryland 301881 52778 17.48 49933.34
Georgia 465525 47063 10.11 43845.39
Virginia 315391 44607 14.14 36950.42
Connecticut 250046 42201 16.88 70133.48
Louisiana 375109 39916 10.64 80689.53
Ohio 390908 35513 9.08 33442.10
Indiana 261546 34574 13.22 38849.89
North Carolina 416289 28785 6.91 39691.62
Colorado 180627 26364 14.60 31365.74
Minnesota 249519 24850 9.96 44243.84
Tennessee 435977 22566 5.18 63803.00
Washington 354354 21702 6.12 46534.34
Arizona 225206 19936 8.85 29574.41
Iowa 156296 19552 12.51 49538.05
Wisconsin 268506 18403 6.85 46115.77
Alabama 217553 17952 8.25 44369.73
Mississippi 171837 15523 9.03 57738.04
Rhode Island 154493 14928 9.66 145836.03
Nebraska 101142 14101 13.94 52285.76
Missouri 193561 13438 6.94 31537.80
South Carolina 200216 11861 5.92 38886.60
Utah 213914 9797 4.58 66723.89
Kentucky 213753 9704 4.54 47844.37
Kansas 94949 9700 10.22 32591.41
Delaware 60671 9498 15.65 62305.65
District of Columbia 46483 8801 18.93 65863.36
Nevada 142560 8628 6.05 46283.37
New Mexico 194447 7689 3.95 92733.84
Arkansas 129515 7253 5.60 42916.67
Oklahoma 193206 6418 3.32 48826.74
South Dakota 44128 4993 11.31 49881.37
New Hampshire 70280 4651 6.62 51687.45
Oregon 129201 4243 3.28 30632.78
Puerto Rico 3776 3776 100.00 1182.33
Idaho 46697 2839 6.08 26057.65
North Dakota 72040 2577 3.58 94532.99
Maine 49609 2325 4.69 36905.64
West Virginia 97622 2010 2.06 54624.49
Vermont 33970 981 2.89 54440.06
Wyoming 24393 903 3.70 42147.08
Hawaii 54620 652 1.19 38576.93
Montana 39798 515 1.29 37236.92
Alaska 51695 459 0.89 70665.51

In Depth India Stats (State Wise Figures)

Confirmed Cases and Deaths (States of India)

State Confirmed NewConfirmations CasesPercentIncrease Recovered RecoveryRate Active Deaths NewDeaths DeathsPercentIncrease FatalityRate
Maharashtra 67655 2487 3.82 29329 43.35 36040 2286 89 4.05 3.38
Tamil Nadu 22333 1149 5.42 12757 57.12 9400 176 13 7.98 0.79
Delhi 19844 1295 6.98 8478 42.72 10893 473 57 13.70 2.38
Gujarat 16794 438 2.68 9919 59.06 5837 1038 31 3.08 6.18
Rajasthan 8831 214 2.48 6032 68.30 2604 195 2 1.04 2.21
Madhya Pradesh 8089 198 2.51 4842 59.86 2897 350 7 2.04 4.33
Uttar Pradesh 8075 374 4.86 4843 59.98 3015 217 4 1.88 2.69
State Unassigned 5630 139 2.53 0 0.00 5630 0 0 NaN 0.00
West Bengal 5501 371 7.23 2157 39.21 3027 317 8 2.59 5.76
Bihar 3807 242 6.79 1520 39.93 2264 23 2 9.52 0.60
Andhra Pradesh 3571 110 3.18 2340 65.53 1169 62 2 3.33 1.74
Karnataka 3221 299 10.23 1218 37.81 1950 51 2 4.08 1.58
Telangana 2698 199 7.96 1428 52.93 1188 82 5 6.49 3.04
Jammu and Kashmir 2446 105 4.49 927 37.90 1491 28 0 0.00 1.14
Punjab 2263 30 1.34 1987 87.80 231 45 1 2.27 1.99
Haryana 2091 168 8.74 1048 50.12 1023 20 0 0.00 0.96
Odisha 1948 129 7.09 1126 57.80 813 9 0 0.00 0.46
Assam 1340 123 10.11 186 13.88 1147 4 0 0.00 0.30
Kerala 1270 61 5.05 590 46.46 670 10 0 0.00 0.79
Uttarakhand 907 158 21.09 102 11.25 797 5 0 0.00 0.55
Jharkhand 635 72 12.79 256 40.31 374 5 0 0.00 0.79
Chhattisgarh 503 56 12.53 114 22.66 388 1 0 0.00 0.20
Himachal Pradesh 330 17 5.43 109 33.03 212 6 0 0.00 1.82
Tripura 316 45 16.61 173 54.75 143 0 0 NaN 0.00
Chandigarh 293 4 1.38 199 67.92 90 4 0 0.00 1.37
Ladakh 77 0 0.00 47 61.04 30 0 0 NaN 0.00
Goa 71 1 1.43 44 61.97 27 0 0 NaN 0.00
Manipur 71 11 18.33 11 15.49 60 0 0 NaN 0.00
Puducherry 70 13 22.81 25 35.71 45 0 0 NaN 0.00
Nagaland 43 7 19.44 0 0.00 43 0 0 NaN 0.00
Andaman and Nicobar Islands 33 0 0.00 33 100.00 0 0 0 NaN 0.00
Meghalaya 27 0 0.00 12 44.44 14 1 0 0.00 3.70
Arunachal Pradesh 4 1 33.33 1 25.00 3 0 0 NaN 0.00
Dadra and Nagar Haveli and Daman and Diu 2 0 0.00 1 50.00 1 0 0 NaN 0.00
Mizoram 1 0 0.00 1 100.00 0 0 0 NaN 0.00
Sikkim 1 0 0.00 0 0.00 1 0 0 NaN 0.00
Lakshadweep 0 0 NaN 0 NaN 0 0 0 NaN NaN

In Depth Italy Stats (Region Wise Figures)

Confirmed Cases and Deaths- Regions of Italy (With Fatality and Confirmation Rates)

Region Swabs Confirmations NewConfirmations CasesPercentIncrease ConfirmationRate HospitalizedWithSymptoms IntensiveCare ActiveCases Deceased FatalityRate
Lombardia 753874 88968 210 0.24 11.80 3131 170 20996 16112 18.11
Piemonte 319133 30637 54 0.18 9.60 973 58 5161 3867 12.62
Emilia-Romagna 325482 27790 31 0.11 8.54 393 57 3163 4114 14.80
Veneto 669768 19152 6 0.03 2.86 112 6 1500 1918 10.01
Toscana 252090 10104 4 0.04 4.01 97 28 1111 1041 10.30
Liguria 106363 9663 12 0.12 9.08 195 8 669 1465 15.16
Lazio 255474 7728 13 0.17 3.02 730 57 2983 735 9.51
Marche 103634 6730 3 0.04 6.49 62 9 1338 987 14.67
Campania 201543 4802 5 0.10 2.38 227 5 980 412 8.58
Puglia 118652 4494 4 0.09 3.79 143 11 1177 504 11.21
P.A. Trento 88558 4430 1 0.02 5.00 13 3 304 462 10.43
Sicilia 150054 3443 1 0.03 2.29 65 7 986 274 7.96
Friuli Venezia Giulia 134378 3273 2 0.06 2.44 41 1 278 333 10.17
Abruzzo 75652 3222 7 0.22 4.26 104 4 753 405 12.57
P.A. Bolzano 66247 2597 1 0.04 3.92 13 4 127 291 11.21
Umbria 70553 1431 0 0.00 2.03 15 2 31 76 5.31
Sardegna 57296 1356 0 0.00 2.37 33 2 185 130 9.59
Valle d’Aosta 15203 1184 1 0.08 7.79 12 0 15 143 12.08
Calabria 70274 1158 0 0.00 1.65 22 1 144 97 8.38
Molise 14631 436 0 0.00 2.98 2 2 145 22 5.05
Basilicata 29880 399 0 0.00 1.34 4 0 29 27 6.77

In Depth Canada Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of Canada (With Fatality Rates)

Province Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
Quebec 51059 408 0.81 4641 202 4.55 9.09 5980.43 543.59 1 in 167
Ontario 29390 367 1.26 2344 12 0.51 7.98 1997.71 159.33 1 in 501
Alberta 7010 18 0.26 143 0 0.00 2.04 1588.44 32.40 1 in 630
British Columbia 2573 0 0.00 164 0 0.00 6.37 503.43 32.09 1 in 1986
Nova Scotia 1056 0 0.00 60 0 0.00 5.68 1080.35 61.38 1 in 926
Saskatchewan 646 1 0.16 11 1 10.00 1.70 546.69 9.31 1 in 1829
Manitoba 295 1 0.34 7 0 0.00 2.37 214.15 5.08 1 in 4670
Newfoundland and Labrador 261 0 0.00 3 0 0.00 1.15 500.61 5.75 1 in 1998
New Brunswick 132 3 2.33 0 0 NaN 0.00 169.23 0.00 1 in 5909
Prince Edward Island 27 0 0.00 0 0 NaN 0.00 170.72 0.00 1 in 5858
Yukon 11 0 0.00 0 0 NaN 0.00 267.78 0.00 1 in 3734
Northwest Territories 5 0 0.00 0 0 NaN 0.00 111.35 0.00 1 in 8981

In Depth China Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of China (With Fatality Rates)

Province Confirmed Deaths FatalityRate
Hubei 68135 4512 6.62
Guangdong 1595 8 0.50
Henan 1276 22 1.72
Zhejiang 1268 1 0.08
Hong Kong 1084 4 0.37
Hunan 1019 4 0.39
Anhui 991 6 0.61
Heilongjiang 945 13 1.38
Jiangxi 937 1 0.11
Shandong 792 7 0.88
Shanghai 672 7 1.04
Jiangsu 653 0 0.00
Beijing 593 9 1.52
Chongqing 579 6 1.04
Sichuan 575 3 0.52
Fujian 358 1 0.28
Hebei 328 6 1.83
Shaanxi 308 3 0.97
Guangxi 254 2 0.79
Inner Mongolia 235 1 0.43
Shanxi 198 0 0.00
Tianjin 192 3 1.56
Yunnan 185 2 1.08
Hainan 169 6 3.55
Jilin 155 2 1.29
Liaoning 149 2 1.34
Guizhou 147 2 1.36
Gansu 139 2 1.44
Xinjiang 76 3 3.95
Ningxia 75 0 0.00
Macau 45 0 0.00
Qinghai 18 0 0.00
Tibet 1 0 0.00

Time Series Curves (Top 20 Countries with the Highest Cases)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most confirmed COVID-19 cases as of today in decreasing order of confirmations.

Confirmed Cases Count (Linear)

Country Wise Time Series Curve

Confirmed Cases Count (Logarithmic)

Country Wise Time Series Curve

Time Series Curves (Top 20 Countries with the Highest Deaths)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most COVID-19 deaths as of today in decreasing order of confirmations.

Death Count (Linear)

Country Wise Time Series Curve

Death Count (Logarithmic)

Country Wise Time Series Curve

Epidemic Curve: Delta in the past 24 hrs (Top 20 Countries with the Highest Cases)

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various countries. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 countries in the world as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Delta in Confirmed Cases

Number of New Cases in the past 24 hrs

Delta in Deaths

Number of Deaths in the past 24 hrs

Measuring Outbreak Velocity: 5 Day Lagging Average Doubling Time (Top 20 Countries with the Highest Cases)

The velocity of an outbreak is determined by a construct known as doubling time. This value describes the number of days, on average, required for the number of cases to double in a given area. For our analysis we use average doubling time, which can be defined as the number of days, on average, required for the average number of COVID-19 cases to double in a given area.

This measure can describe COVID-19 behavior worldwide, in a country, or even in a smaller region such as a state. For our analysis, we will discuss average doubling time at a national level for the top 20 most affected countries.

Below, we have calculated average doubling time for several nations, on a trailing, rolling 5-day basisbased on today’s case values. A decline in average doubling time indicates that the COVID-19 outbreak (confirmation rate) is accelerating (average cases double in fewer days), while an increase of average doubling time indicates that the outbreak is slowing.

Ideally, when social distancing and lockdowns are implemented aggressively in a country and after some period of delay, doubling times should begin to increase in a matter of days, weeks, or months, depending upon the severity of the epidemic and the degree of social distancing achievable.

Given the fact that many countries across the world have already enacted or implemented social distancing measures, this is why one should be cautious not to extrapolate COVID-19 growth rates from trailing statistics.

5 Day Lagging Avg Doubling Time of Confirmations

Confirmed Cases and Deaths Per Million Population and Infection Odds

This metric confirmed cases per million population and deaths per million population shows the extent to which the disease has spread with respect to the population of the country. The metric Infection Odds shows 1 in how many people are infected with COVID-19 in the corresponding country.

For the top 20 countries with most confirmed cases excluding cruise ships

Country_Region ConfirmedCasesPerMillionPopl DeathsPerMillionPopl InfectionOdds
US 5471.19 319.01 1 in 183
Brazil 2459.86 140.06 1 in 407
Russia 2808.60 32.48 1 in 356
United Kingdom 4156.47 580.54 1 in 241
Spain 5132.43 581.38 1 in 195
Italy 3852.46 552.50 1 in 260
India 142.35 4.04 1 in 7025
France 2821.45 429.99 1 in 354
Germany 2215.36 103.15 1 in 451
Peru 5112.71 140.07 1 in 196
Turkey 2028.73 56.18 1 in 493
Iran 1866.26 96.07 1 in 536
Chile 5522.88 58.39 1 in 181
Canada 2460.20 196.17 1 in 406
Mexico 701.73 76.86 1 in 1425
Saudi Arabia 2588.37 15.27 1 in 386
China 60.71 3.35 1 in 16471
Pakistan 352.77 7.53 1 in 2835
Belgium 5121.14 830.44 1 in 195
Qatar 21564.99 14.40 1 in 46

US Detailed State and County Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the state/ county level in USA.

Epidemic Curve: Delta in Confirmed Cases in US States

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various US states. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 states in USA as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in US States

Number of Deaths in the past 24 hrs

Top 50 US Counties with the Highest Cases and Deaths

All NYC boroughs are mentioned together as New York County

County State Confirmations Deaths FatalityRate
New York New York 203303 21569 10.61
Cook Illinois 77925 3642 4.67
Los Angeles California 55001 2362 4.29
Nassau New York 40396 2122 5.25
Suffolk New York 39643 1901 4.80
Westchester New York 33481 1371 4.09
Philadelphia Pennsylvania 22629 1316 5.82
Middlesex Massachusetts 21287 1615 7.59
Wayne Michigan 20415 2461 12.05
Hudson New Jersey 18767 1183 6.30
Bergen New Jersey 18272 1579 8.64
Miami-Dade Florida 18000 700 3.89
Suffolk Massachusetts 17936 871 4.86
Essex New Jersey 17649 1664 9.43
Passaic New Jersey 16170 928 5.74
Middlesex New Jersey 15921 994 6.24
Union New Jersey 15821 1073 6.78
Fairfield Connecticut 15549 1277 8.21
Prince George’s Maryland 15220 541 3.55
Essex Massachusetts 14225 925 6.50
Rockland New York 13151 631 4.80
Harris Texas 12276 232 1.89
Montgomery Maryland 11361 612 5.39
New Haven Connecticut 11323 972 8.58
Fairfax Virginia 11110 383 3.45
Providence Rhode Island 11052 0 0.00
Worcester Massachusetts 11018 767 6.96
Orange New York 10406 444 4.27
Hartford Connecticut 10296 1250 12.14
Dallas Texas 10234 229 2.24
Marion Indiana 9853 578 5.87
Maricopa Arizona 9815 432 4.40
District of Columbia District of Columbia 8801 466 5.29
Ocean New Jersey 8748 739 8.45
Oakland Michigan 8396 988 11.77
Hennepin Minnesota 8393 613 7.30
Lake Illinois 8331 291 3.49
Monmouth New Jersey 8219 597 7.26
King Washington 8092 567 7.01
Norfolk Massachusetts 8079 821 10.16
Plymouth Massachusetts 7859 552 7.02
Milwaukee Wisconsin 7750 299 3.86
DuPage Illinois 7707 373 4.84
Jefferson Louisiana 7584 450 5.93
Riverside California 7486 323 4.31
San Diego California 7481 269 3.60
Bristol Massachusetts 7159 415 5.80
Orleans Louisiana 7127 507 7.11
Broward Florida 7123 313 4.39
Montgomery Pennsylvania 7061 684 9.69

Overall US Choropleth Map

Choropleths are an ideal way to visualize the past/ current COVID-19 hotspots within a country. The below are the hotspots in the US.

County level COVID-19 Confirmations Map

Canada Detailed Province Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the province level in Canada.

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in the most affected Canadian provinces- Quebec, Ontario, Alberta and British Columbia. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Epidemic Curve: Delta in Confirmed Cases in Canadian Provinces

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in Canadian Provinces

Number of Deaths in the past 24 hrs

Data Sources

CSSEGISandData, The NY Times, amodm/api-covid19-in and pcm-dpc